Title :
Three-Dimensional Compton Imaging Using List-Mode Maximum Likelihood Expectation Maximization
Author :
Tornga, Shawn R. ; Sullivan, M.W.R. ; Sullivan, Mohini W Rawool
Author_Institution :
Los Alamos Nat. Lab., Los Alamos, NM
fDate :
6/1/2009 12:00:00 AM
Abstract :
Compton imaging is a gamma ray imaging technique that has many possible applications including homeland security and medical imaging. Using the Compton scattering formula the origin of a scattered gamma-ray can be localized to a point on the surface of a cone using a minimum of two position and energy measurements. List-mode Maximum likelihood expectation maximization (MLEM) is an iterative statistical algorithm that makes successive approximations to the most probable source distribution that would have led to the observed data. Conventional MLEM is often performed in two dimensions, which still requires knowledge of the source-to-detector distance. We propose iteration over all three spatial dimensions in order to maximize the probability in three-dimensional space. This paper reports on the development of a three-dimensional MLEM (3DMLEM) algorithm to reconstruct images from a Compton imager in three dimensions for single, multiple and line sources. Several techniques for reducing convergence times are also discussed.
Keywords :
Compton effect; biomedical imaging; gamma-ray detection; image reconstruction; maximum likelihood estimation; 3D Compton imaging; convergence; gamma ray imaging technique; homeland security; iterative statistical algorithm; list-mode maximum likelihood expectation maximization; medical imaging; source-to-detector distance; Biomedical imaging; Convergence; Energy measurement; Image reconstruction; Iterative algorithms; Nuclear imaging; Optical imaging; Probability; Scattering; Terrorism; Algorithms; compton scattering; nuclear imaging;
Journal_Title :
Nuclear Science, IEEE Transactions on
DOI :
10.1109/TNS.2008.2007951